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Autore: | Ding Zhengming |
Titolo: | Learning Representation for Multi-View Data Analysis : Models and Applications / / by Zhengming Ding, Handong Zhao, Yun Fu |
Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Edizione: | 1st ed. 2019. |
Descrizione fisica: | 1 online resource (272 pages) |
Disciplina: | 006.31 |
Soggetto topico: | Data mining |
Artificial intelligence | |
Pattern recognition | |
Data Mining and Knowledge Discovery | |
Artificial Intelligence | |
Pattern Recognition | |
Persona (resp. second.): | ZhaoHandong |
FuYun | |
Nota di contenuto: | Introduction -- Multi-view Clustering with Complete Information -- Multi-view Clustering with Partial Information -- Multi-view Outlier Detection -- Multi-view Transformation Learning -- Zero-Shot Learning -- Missing Modality Transfer Learning -- Deep Domain Adaptation -- Deep Domain Generalization. . |
Sommario/riassunto: | This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision. |
Titolo autorizzato: | Learning Representation for Multi-View Data Analysis |
ISBN: | 3-030-00734-0 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910337849103321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |